Applied Scientist, Experience Analytics

Amazon • Seattle, WA

1d • Onsite

About The Position

AWS Experience Analytics (EXA) is seeking an Applied Scientist to join their team. EXA focuses on transforming customer understanding into products and intelligence for AWS teams. They are building a unified customer lifecycle data platform, customer experience measurement frameworks, and segmentation systems. The role requires someone to contribute to signal analysis, pattern discovery, and predictive modeling, possessing both scientific depth and production engineering skills to deploy models. The ideal candidate will have a curious mindset and contribute to the team's ML work at scale, addressing the evolving needs of AWS customers who are shifting towards AI-augmented and autonomous workflows. The role involves framing and tackling new modeling problems, particularly those related to behavioral signals from AI agents and agentic workflows, and extending or inventing scientific techniques when necessary, balancing rigor with speed.

Requirements

• PhD
• 3+ years of experience building and deploying ML models into production systems
• Experience programming in Python or equivalent, with production-quality code
• Experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and ML infrastructure (training pipelines, model serving, monitoring)
• PhD in computer science, machine learning, statistics, operations research, or a related quantitative field

Nice To Haves

• Experience with customer analytics, behavioral segmentation, or user modelling at scale
• Experience with real-time ML systems (online scoring, streaming data, anomaly detection)
• Experience working with large-scale customer data platforms or data lake architectures

Responsibilities

• Contribute to and extend the team's work in signal analysis, pattern discovery, and predictive modelling — adding scientific depth and production engineering capability.
• Build production ML infrastructure — offline training pipelines, online scoring systems, and monitoring.
• Frame and tackle new modelling problems as they emerge — particularly around behavioral signals from AI agents and agentic workflows.
• Extend and invent scientific techniques where needed, while also knowing when existing approaches are sufficient, and speed matters more than novelty.
• Collaborate with engineers building the CLARA platform, the Experience Metrics Framework, and the Customer Segmentation Framework to ensure ML systems integrate cleanly and serve the broader product vision.
• Contribute to the team's scientific direction — proposing new modelling initiatives, sharing approaches, and helping the team make good trade-offs between rigor and velocity.
• Mentor others and contribute to the broader applied science community.
• Write clear technical documentation describing your approaches, trade-offs, and results.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree